This Mentored Research Scientist Career Development Award will afford Dr. Rohan Palmer focused training for his programmatic line of research in the genetics of alcohol dependence and related phenotypes (AD). Given that gene identification studies (in particular genomewide association studies) on alcoholism are challenged by the fact that alcoholism is a multifactorial disorder influenced by multiple interacting genes, each with small effect, the public health relevance for deriving new analytical strategies and statistical methods is substantial. The proposed research aligns with the National Institute for Alcohol Abuse and Alcoholism's plan to Identify genes associated with vulnerability for alcohol dependence by employing new and emerging technologies, on samples from study populations previously recruited for genetic research on alcohol dependence. It is evident that a network-based approach is necessary to describe the joint distribution of genetic effects that comprise specific neural or molecular pathways that underlie alcohol dependence. Genetic samples and phenotypic data available through the Database for Genotype and Phenotypes (dbGAP), as well as collected data from the Center for Antisocial Drug Dependence will be used to provide a cost-effective opportunity to identify gene networks that alter susceptibility to AD, thereby improving our understanding of AD while introducing a novel approach to the field of alcohol genetics. The proposed research assists Dr. Palmer in achieving his career and training goals to: (1) develop proficiency in statistical genetics and systems-based association methods, (2) become adept at using biostatistics tools to identify gene and protein interaction networks, (3) identify variation in evolutionarily robust biological systems by developing novel data mining techniques, (4) develop a program of research aimed at identifying combinations of genetic variation in biological systems affected by alcohol and other drug/pharmaceuticals with the potential for abuse, and (5) establish collaborations to develop high-quality research manuscripts and grants. The specific aims of the proposed research are to: (1) Derive gene network graphs that describe the relationships between genes (i.e., influence graphs) using prior knowledge of genetic association, bioinformatics databases, systems biology, and gene and protein interaction modeling tools; (2) identify sub networks of genes within the influence graphs from Aim 1 (these networks will be identified before and after accounting for several covariates (e.g., major depression, and select environmental factors); and (3) replicate findings from Aim 2 using independent samples with similar phenotypic and genetic data. Training and research goals will be achieved through a combination of didactic coursework, ongoing close mentorship, mentored research, workshops, and collaborative projects. This application will lead to research findings to support planned future R01s, as well as innovative research methods that advance our understanding of gene-biology-phenotype relationships.